Information about Asia and the Pacific Asia y el Pacífico
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Chapter 9. Monetary Policy Frameworks: An Assessment

Author(s):
Alfred Schipke
Published Date:
April 2015
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Information about Asia and the Pacific Asia y el Pacífico
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Author(s)
Ashvin Ahuja, Nombulelo Duma, Sarwat Jahan, Yasuhisa Ojima and Alexandra Peter 

The key features of frontier and developing Asia’s development experience since the mid-1990s are its impressive growth performance and relatively well-contained inflation.1 During 1995–2012, the median growth rate for frontier and developing Asia has consistently been more robust and less volatile than that in emerging market Asia (Figure 9.1). However, on the inflation front, frontier and developing Asia does not appear to have enjoyed “the great moderation” before the global financial crisis in 2008 like many of the emerging market economies. Nevertheless, the inflation experience has also become more homogeneous across frontier and developing Asia, both in level and volatility (Figure 9.2).

Figure 9.1Growth: Comparison of Frontier and Developing Asia with Emerging Asia

Sources: Penn World Tables v. 7.1; World Bank, PovcalNet; and IMF staff calculations.

Note: The standard deviation measures how spread out numbers are. The higher the standard deviation, the higher the level of volatility. FD = frontier and developing, EM = emerging market.

Figure 9.2Inflation: Comparison of Frontier and Developing Asia with Emerging Asia

Sources: Penn World Tables v. 7.1; World Bank, PovcalNet; and IMF staff calculations.

Note: The standard deviation measures how spread out numbers are. The higher the standard deviation, the higher the level of volatility. FD = frontier and developing, EM = emerging market.

This chapter focuses on the role of monetary and exchange rate policies adopted by countries in the region in determining growth and inflation outcomes. From the institutional point of view, we find that frontier and developing Asian central banks are predominantly exchange rate targeters, which are not operationally autonomous and tend to place more emphasis on supporting growth than on price stability. That said, our empirical work also reveals that the monetary and exchange rate strategies these countries choose—primarily intermediate exchange rate regimes—are conducive to lower inflation without sacrificing the growth achievement, in terms of both the growth rate and growth volatility.

The chapter begins by characterizing and recording the salient facts around monetary policy regime choices in frontier and developing Asia. The next section provides a brief background of the key institutional frameworks for monetary policy to indicate the relative level of institutional quality, which may help explain the policy regime choices made. Next there is an assessment of the impacts of different exchange rate regimes on growth and inflation outcomes in frontier and developing Asia and a comparison with the experiences in low-income countries in other regions. The final section concludes the chapter.

Characterizing Monetary Policy

While low-income countries have shifted more toward flexible exchange rates, exchange rate stability remains the primary objective in the majority of frontier and developing Asia’s central banks. Intermediate exchange rate regimes continue to be predominant in these countries (Figure 9.3).

Figure 9.3Exchange Rate Regimes

(Percent)

Source: Authors’ calculations based on IMF, Annual Report on Exchange Arrangements and Exchange Restrictions database.

In addition, a few frontier and developing Asia central banks pursue other objectives, including promoting economic growth and price stability. In several cases, it remains unclear which objective is the overriding one, and there can be potential conflicts. It is also notable that only a few frontier and developing Asian central banks have price stability as the overriding policy mandate (Bhutan, Papua New Guinea, Timor-Leste). This general lack of focus on price stability is consistent with the relatively high and volatile inflation experience observed during 1995–2012 when compared with emerging Asia (Table 9.1).

Table 9.1Monetary Policy Regime
Exchange Rate TargetingMonetary Aggregate TargetingInflation TargetingDe Facto Exchange Rate RegimeForward Foreign Exchange Market
BangladeshOther managed
BhutanConventional peg
CambodiaStabilized arrangement
Lao P.D.R.Stabilized arrangement
MaldivesStabilized arrangement
MongoliaFloating
MyanmarOther managed
NepalConventional peg
Papua New GuineaFloating
Timor-LesteNo separate legal tender
VietnamStabilized arrangement
Sources: IMF, Annual Report on Exchange Arrangements and Exchange Restrictions database; and IMF staff survey.Note: Mongolia set monetary aggregate targeting during the IMF supported program.
Sources: IMF, Annual Report on Exchange Arrangements and Exchange Restrictions database; and IMF staff survey.Note: Mongolia set monetary aggregate targeting during the IMF supported program.

This primary focus on the exchange rate is consistent with the greater stability of the nominal exchange rate during 1996–2009. Moreover, frontier and developing Asia as a whole has steadily become more financially open.2 These developments come at the expense of the ability to determine short-term domestic interest rates independently.

The group’s experience remains heterogeneous, however, with three distinct policy strategies (Figure 9.4): the first—also the majority—adopts a fixed or intermediate exchange rate regime and retains domestic monetary control at the expense of financial openness. Pursuing this strategy are Bangladesh, Bhutan, Lao P.D.R., Myanmar, Nepal, and Vietnam. The second floats the exchange rate and pursues financial openness while retaining high degrees of domestic monetary control. This group is represented by Mongolia and Papua New Guinea. The third strategy—maintaining a stable exchange rate with increasingly open financial markets—is employed by Cambodia and Maldives.

Figure 9.4The Trilemma Indexes

Source: Updated database based on Aizenman, Chinn, and Ito (2008).

Institutional Frameworks for Monetary Policy

We find that frontier and developing Asia’s institutional frameworks for monetary policy remain rudimentary and that there is a general lack of operational autonomy for central banks.

Central Bank Autonomy

Overall, the degree of operational autonomy of frontier and developing Asian central banks is limited. In some countries, central bank governors are members of the cabinet (Lao P.D.R., Vietnam). In some countries, where there is a central bank board of directors, government representatives could occupy over a third of the board seats (Bangladesh, Bhutan, Myanmar). While monetary policy is determined by the government in some cases (Bhutan, Lao P.D.R.), in others, decisions require government approval (Vietnam, for example). For most central banks, lending to the government is restricted or allowed provided repayment takes place within three to six months. In Timor-Leste, lending to the government is not allowed.

Central banks are mostly granted some level of financial autonomy. In most central banks, the integrity of their capital is protected through a mechanism that allows for compensation from the government. In most cases, the government can issue marketable securities to raise funds to cover a central bank loss. Two of the eleven central banks do not have provisions for the government to cover their losses (Bangladesh, Myanmar). Most central banks can determine their own budget. In the case of Bangladesh, the budget requires approval by a government auditor, while in Cambodia and Vietnam, government approval is required.

Monetary Policy Objectives

The monetary policy regime in most of frontier and developing Asia includes the exchange rate as the nominal anchor. While some countries have the exchange rate clearly specified as the nominal anchor (Bhutan, Cambodia, Maldives, Nepal), a few others have mixed regimes with targets for monetary aggregates (Lao P.D.R., Vietnam; Box 9.1). Timor-Leste is fully dollarized. Cambodia, Lao P.D.R., and Vietnam are partially dollarized.3 Of the exchange-rate-targeting countries, Bhutan and Nepal have conventional pegs to the Indian rupee. Few countries have monetary aggregate targeting as the overarching monetary policy regime (Bangladesh, for example).

Monetary Policy Implementation

Though central banks in most of frontier and developing Asia do not have autonomy to determine monetary policy, they are responsible for its implementation. Few countries have any form of financial programming that guides decisions on monetary policy. Further, the central banks’ autonomy in determining the monetary program varies. In Bangladesh, the governor approves the financial program every July. In the majority of countries, the board of directors decides on the monetary program (Maldives) and/or implements monetary policy (Bangladesh, Bhutan, Cambodia, Maldives, Mongolia, Nepal). In Papua New Guinea, the government proposes the financial program, and the governor is expected to advise or update the minister of finance during its implementation.

Some frontier and developing Asian central banks have liquidity forecasting frameworks. Bhutan, Maldives, Mongolia, Nepal, and Papua New Guinea have some form of liquidity forecasting in place to help guide monetary policy decisions. The frequency of liquidity forecasting varies from daily (Mongolia) to weekly and biweekly (Papua New Guinea). Liquidity forecasting can form a basis for formulating forward-looking monetary policy and support interest rate policy in countries with low levels of dollarization and a functioning monetary transmission mechanism.

Box 9.1The Formulation and Implementation of Monetary Policy in Vietnam

The current framework: Like many frontier and developing Asian economies, Vietnam has a mixed monetary policy regime with elements of both monetary and exchange rate targeting. In formulating policy, the State Bank of Vietnam (SBV) takes the National Assembly’s targets for growth and inflation for the following year as given and estimates the trajectories of monetary aggregates and credit, which it then monitors regularly. A range of instruments—multiple policy interest rates, differentiated reserve requirements, and open market operations—as well as administrative controls are used. In essence, bank credit is an intermediate target, as in monetary-targeting regimes, but the SBV also announces a daily official U.S. dollar–Vietnamese dong exchange rate.

How effective has monetary policy been? To identify the influence of various monetary factors on inflation and growth, a vector autoregressive model is estimated that relates inflation to GDP growth, stock market prices, fuel prices, and monetary factors such as credit growth, interest rates, the nominal effective exchange rate, and the dollar-dong exchange rate during 2005:Q1–2012:Q4. The results suggest that Vietnam’s inflation is a monetary phenomenon; that is, inflation is influenced largely by monetary factors from three quarters onward. However, GDP growth tends to be persistent and is influenced mostly by nonmonetary factors during the first six to eight quarters, complicating monetary policy fine-tuning of growth. Among monetary variables, the exchange rate appears to have a sizable and more immediate pass-through to inflation.

Figure 9.1.1Variance Decomposition of Inflation Process

(Percent)

Sources: Bloomberg, L.P.; IMF, World Economic Outlook database; and Vietnamese authorities.

Notes: NEER = nominal effective exchange rate; USD = U.S. dollar; VND = Vietnamese dong.

What might a more robust framework look like? With a severely impaired credit channel, interest rates and sterilized intervention can be used to support the exchange rate anchor, which would help contain inflation. To help absorb shocks, the exchange rate could be allowed to move in an increasingly wider band. Focusing the SBV’s policy mandate on achieving low and stable inflation over the medium term, increasing its operational autonomy, and strengthening its accountability framework would establish policy credibility. In the medium and long term, it may be necessary to reconsider the status of the SBV and its relationship with the government in the formulation and implementation of monetary policy with a view toward greater central bank autonomy.

Source: Ahuja, Duma, and Ha (2013).

Accountability and Transparency

Accountability and transparency of policies and decisions is lacking in most of the central banks. Few central banks publish their monetary policy decisions immediately after they are made. Most central banks use either their annual reports or other documents to communicate policy decisions to the public. Only Vietnam issues a press release immediately after making monetary policy decisions.

Assessing Economic Performance of Different Monetary Policy Strategies

Introduction

In this section, we analyze how different monetary and exchange rate policy strategies impact macroeconomic performance—specifically how the regimes perform on inflation, per capita GDP growth, and GDP growth volatility outcomes. For this purpose, we rely on the de facto classification of the exchange rate regimes (Table 9.2). This exercise is done for all low-income countries, with a specific focus on frontier and developing Asian economies.

Table 9.2Classification of Low-Income Countries' Exchange Rate Regimes
All Low-Income Countries
De jure classification
Hard pegIntermediateFloating
De facto classification
Hard peg32100
Intermediate1248176
Floating142495
Total323290671
Percentage consensus99.485.573.8
Low-Income Countries Outside Asia and the Pacific
De jure classification
Hard pegIntermediateFloating
De facto classification
Hard peg29700
Intermediate1130113
Floating126408
Total299156521
Percentage consensus99.383.378.3
Low-Income Asia and Pacific Countries
De jure classification
Hard pegIntermediateFloating
De facto classification
Hard peg2400
Intermediate011863
Floating01687
Total24134150
Percentage consensus10088.158.0
Source: Authors’ calculations based on Annual Report on Exchange Arrangements and Exchange Restrictions database.Note: The exchange rate classifications are for the time period 1990-2007. The de facto classification is based on Bubula and Ötker-Robe (2002) for the period before 1999 and on the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) for the period after 1999. The de jure classification is based on the period before 1999 and on Anderson (2009) for the period after 1999. Definitions of hard peg, intermediate, and floating regime can be found in Appendix Table A9.1.
Source: Authors’ calculations based on Annual Report on Exchange Arrangements and Exchange Restrictions database.Note: The exchange rate classifications are for the time period 1990-2007. The de facto classification is based on Bubula and Ötker-Robe (2002) for the period before 1999 and on the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER) for the period after 1999. The de jure classification is based on the period before 1999 and on Anderson (2009) for the period after 1999. Definitions of hard peg, intermediate, and floating regime can be found in Appendix Table A9.1.

Traditionally, the discussion about exchange rate regimes has revolved around the trade-off between a credible regime and the power to control monetary policy independently so as to insulate the economy from shocks. This debate has shifted recently to discussing the trade-off between inflation and growth (Calderon and Schmidt-Hebbel 2003). A fixed exchange rate may improve the credibility of monetary policy and lower inflation, whereas it is asserted that flexible exchange rates are able to enhance growth and reduce output volatility by allowing the exchange rate to work as a shock absorber (Calderon and Schmidt-Hebbel 2003; Levy-Yeyati and Sturzenegger 2003). However, it is also possible that flexible exchange rates add to economic volatility. Growth could be higher over time under fixed regimes due to lower transaction costs, interest rates, and uncertainty (Rogoff and others 2004).

Empirical studies analyzing the effects of exchange rate regimes on macroeco-nomic performance have not yielded conclusive answers. Depending on the exchange rate classification methodology, time period used, and country sample, fixed, flexible, or intermediate regimes deliver the best economic performance (Frankel 2010; Rogoff and others 2004). For example, Ghosh, Gulde, and Wolf (2003) find fixed exchange rate regimes associated with significantly lower inflation, but no significant effect on economic growth (using a de jure classification); Levy-Yeyati and Sturzenegger (2003) find higher growth under flexible exchange rates (using their de facto classification).4

We find that a country’s choice of exchange rate regimes can have a significant effect on the inflation outcome in that country, but the effects on economic growth and output volatility appear to be smaller and not always statistically significant. The effects for frontier and developing Asia by and large appear to be similar to those observed in other regions. Specifically, our results show that hard pegs and intermediate regimes are associated with significantly lower inflation compared with floating regimes. However, intermediate regimes are not associated with significantly different GDP growth or growth volatility compared with floating regimes. Hard pegs, on the other hand, are associated with lower output volatility than floating regimes, but also with weaker growth.

Data and Regression Setup

To assess how exchange rate regimes affect economic performance, we regress the de facto exchange rate regimes on three performance indicators: inflation, per capita real GDP, and real GDP growth volatility, controlling for other factors that influence these indicators. To exclude the recent financial crisis period, the sample period is 1990–2008. The sample includes all countries on the Poverty Reduction Growth Trust list as of 2008, which covers 78 countries.5

The data used in this regression are mostly drawn from the IMF’s World Economic Outlook database. Table A9.1 provides a detailed description of all variables used in the regression and their sources.

The regression specification follows Calderon and Schmidt-Hebbel (2003). To check for robustness, we also use the determinants specified in Ghosh, Gulde, and Wolf (2003) and Rogoff and others (2004), noted as Specification 2. Since macroeconomic performance could also influence the choice of a particular exchange rate regime, our setup controls for endogeneity. First, a multinomial logit is estimated for hard pegs and intermediate regimes, treating “floating” as the numeraire. In a second step, these adjusted probabilities are used in an instrumental-variable (IV) regression for inflation, GDP per capita growth, and output volatility.6 All regressions include time fixed effects.

The multinomial logit regression’s independent variables are widely used in the literature (for example, see Poirson 2001; Juhn and Mauro 2002; and Rogoff and others 2004, for an overview) and specified in Calderon and Schmidt-Hebbel (2003). In particular, we use the relative size of a country compared to the United States, a country’s geographical area, its ratio of international reserves to imports, the ratio of quasimoney to money, the degree of trade openness, and dummies for landlocked countries and islands.7

Our baseline regression for inflation has the following form:

Inflation πt is defined as πCPI/(1+πCPI), in which πCPI is the rate of change of the consumer price index. HPeg and int are dummies that represent the exchange rate anchor, which are hard peg or intermediate regime, respectively. These two regimes are compared against the base regime, the floating regime. We control other factors that influence inflation, such as lagged inflation (πt–1), money growth (Δm), real GDP growth (Δg), and trade openness (TO).

The regression for per capita growth follows a similar setup:

The determinants of GDP growth include the two dummies for the exchange rate regime, the lagged value of GDP growth, and the degree of openness. In addition, we include the investment ratio (InvestR), terms-of-trade shocks (TOT), the fiscal balance (GB), and the tax ratio (Tax).

Finally, the baseline equation for output volatility is

in which we use the same determinants as in the growth regression, except that the volatilities of the investment ratio and of the terms of trade are used instead of their levels. Volatilities are defined as the three-year centered standard deviation of the variables.

We also include a dummy variable (APD) for frontier and developing Asian economies, both independently and interacted with the exchange rate regime dummy, to measure the difference between these economies and other low-income countries’ predictions. However, we do not include the only hard peg in frontier and developing Asia in this exercise due to data limitations.

Results

The impact of exchange rate regimes on inflation, GDP growth, and output volatility are shown in Figures 9.5, 9.6, and 9.7 and Tables 9.3, 9.4, and 9.5. The coefficients on the dummy variables for hard peg and intermediate regime represent the impact of the respective regime relative to the floating exchange rate regime. Similarly, the coefficient on the APD dummy shows how the economic performance of Asian frontier economies with floating regimes differs from the economic performance of other countries with floating regimes. How Asian frontier economies with intermediate regimes perform compared with other countries with floating regimes is shown by the sum of the coefficients of the intermediate regime dummy, the APD dummy, and the interaction term.

We find a statistically significant negative impact of hard pegs and intermediate regimes on inflation. Countries with a hard peg or an intermediate regime are associated with inflation rates that are 5.3 percent and 6.1 percent lower than countries with a floating regime (Figure 9.5). This result is robust to including a dummy for frontier and developing Asia. In that regression, the coefficient for hard pegs does not change, but intermediate regimes in other regions are now associated with even lower inflation of 8.6 percent compared with floating regimes in other regions. Frontier and developing Asian economies with an intermediate regime have lower inflation of 3.9 percent, and Asian frontier economies with a floating regime have 1.5 percent lower inflation than countries in other regions with a floating regime. However, these results are not statistically significant.

Figure 9.5Inflation Performance across Regimes

(Percent)

Source: Authors’ calculations.

Note: *, **, and *** denote statistical significance at 10 percent, 5 percent, and 1 percent levels, respectively.

The effects of exchange rate regime choices on inflation are in line with results by Rogoff and others (2004), which rely on the de facto exchange rate regime measure developed in Reinhart and Rogoff (2004); by Ghosh, Gulde, and Wolf (2003), who find similar results using de jure exchange rate regimes; and by Ghosh Ostry, and Tsangarides (2010). The other determinants in our regression have the expected coefficients and signs, except for trade openness (Table 9.3). Lagged inflation significantly and positively affects current inflation. Money growth has a small, but positive effect, whereas higher real GDP growth leads to lower inflation.

Table 9.3Inflation
BaselineBaseline with Financial OpennessSpecificationLagged Exchange Rate RegimesExcluding Small States
Hard peg−0.053−0.051−0.041−0.039−0.067−0.082−0.099−0.087
(−2.25)**(−1.69)*(−1.85)*(−1.33)(−3.10)***(−2.37)**(−1.48)(−1.29)
Intermediate regime−0.061−0.086−0.054−0.073−0.143−0.222−0.090−0.094
(−3.46)***(−2.94)***(−3.29)***(−2.70)***(−4.92)***(−3.59)***(−1.71)*(−1.63)
APD−0.015−0.013−0.030−0.031−0.026
(−0.88)(−0.77)(−1.21)(−1.90)*(−0.84)
APD intermediate0.0620.0490.1640.072
regime(1.91)*(1.60)(2.61)***
Lagged inflation0.6120.6250.6100.6230.6310.6500.5730.591
(12.78)***(12.04)***(11.80)***(10.74)***(13.71)***(12.80)***(8.34)***(9.11)***
Money growth0.0090.0090.0090.0090.0340.0320.0080.0080.0090.009
(3.97)**(3.81)***(4.03)***(3.87)***(1.52)(1.44)(4.51)***(4.22)***(3.85)***(3.81)***
Real GDP growth−0.183−0.191−0.135−0.142−0.196−0.285−0.181−0.193−0.225−0.223
(−2.74)***(−2.71)***(−2.15)**(−2.15)**(−1.60)(−1.91)*(−2.74)***(−2.78)***(−2.66)***(−2.67)***
Trade openness0.0080.0070.0120.0120.0100.0080.0080.0100.0110.016
(1.33)(1.12)(1.97)**(1.61)(1.14)(0.66)(1.40)(1.40)(1.34)(2.02)**
Financial openness−0.005−0.005
(−2.33)**(−1.85)*
Government balance−0.359−0.376
(−3.27)***(−2.83)***
Terms-of-trade growth0.0500.055
(1.83)*(2.04)**
Lagged hard peg−0.043−0.042
(−1.96)*(−1.42)
Lagged intermediate−0.049−0.083
regime(−2.85)***(−2.81)***
APD lagged0.090
intermediate regime(2.73)***
Observations113311331106110665365310821082942942
R-squared0.720.700.710.690.080.720.700.680.69
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia, f-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia, f-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.

We perform four robustness checks. First, we include an indicator for financial openness.8 The coefficients on the exchange rate regime are slightly smaller, but still significant except the coefficient on hard pegs in the regression including the APD dummy. Financial openness itself has a significant negative, but small (0.5 percent), impact on inflation.

Second, we conduct the regression using the determinants as specified in Ghosh, Gulde, and Wolf (2003) and Rogoff and others (2004).9 This specification gives higher coefficients for the exchange rate regimes, but intermediate regimes are still associated with a better inflation outcome compared with hard pegs. Third, the results are also robust to using two-year lagged exchange rate regimes, in which case the coefficients are slightly smaller, but still significant. Last, excluding small states (defined as countries with a population less than 1 million) has some impact on the results compared with the baseline regression. The coefficients are somewhat higher, but only intermediate regimes have a significant coefficient in this setup.

Next, the result for economic growth shows that only hard peg regimes seem to have a significant impact on the growth performance relative to the “floaters” (Table 9.4; Figure 9.6). Specifically, the baseline regression shows that hard pegs are associated with significant lower growth compared with floating regimes (3.2 percent). Intermediate regimes, on the other hand, have a positive, but not statistically significant, coefficient. Similarly, there is no significant difference between Asian frontier economies compared with other regions’ floating regimes in terms of growth performance. Our results compare well with those of Rogoff and others (2004), who do not find a statistically significant impact of exchange rate regimes on growth for developing economies—although their results also suggest that growth declines with increased exchange rate flexibility. The results of Ghosh, Gulde, and Wolf (2003) suggest that pegged regimes are associated with higher growth for lower-income countries; however, they use de jure exchange rate measures. Ghosh, Ostry, and Tsangarides (2010), on the other hand, also find some evidence of slower growth under pegged exchange rate regimes.

Table 9.4Real GDP Per Capita Growth
BaselineBaseline with Financial OpennessSpecificationLagged Exchange Rate RegimesExcluding Small States
Hard peg−0.032−0.033−0.031−0.0330.0790.063−0.044−0.046
(−3.07)***(−2.44)**(−2.86)***(−2.25)**(1.34)(1.19)(−2.06)**(−1.97)**
Intermediate regime0.0180.0350.0260.0490.0350.028−0.009−0.010
(0.99)(0.95)(1.17)(1.12)(1.62)(0.94)(−0.49)(−0.43)
APD0.000−0.0030.0280.000−0.007
(0.00)(−0.34)(1.90)*(0.05)(−0.65)
APD intermediate−0.032−0.041−0.0240.011
regime(−0.84)(−0.94)(−0.80)(0.44)
Lagged growth0.2740.2680.2670.2580.2820.2850.3420.343
(3.79)***(3.69)***(3.65)***(3.47)***(3.83)***(3.90)***(3.94)***(4.04)***
Investment ratio0.1000.1150.0930.1130.0150.0430.1010.1150.0770.072
(3.85)***(3.26)***(3.44)***(2.97)***(0.24)(0.73)(3.79)***(3.12)***(3.10)***(2.91)***
Trade openness0.0130.0200.0180.0310.0300.0130.0130.0200.0050.008
(2.03)**(1.64)(2.46)**(1.82)*(1.95)*(1.06)(2.01)**(1.52)(0.71)(0.94)
Terms of trade growth0.0200.0190.0220.0230.0070.0060.0180.0140.0340.035
(0.99)(0.86)(1.01)(0.93)(0.22)(0.19)(0.83)(0.59)(1.45)(1.44)
Tax ratio−0.137−0.185−0.159−0.233−0.020−0.013−0.135−0.1 76−0.099−0.102
(−3.35)***(−2.10)**(−3.23)***(−2.09)**(−0.23)(−0.10)(−3.02)***(−1.96)*(−3.05)***(−2.03)**
Government balance0.1270.1250.1400.141−0.0160.0220.1300.1230.1390.138
(2.77)***(2.60)***(2.74)***(2.52)**(−0.17)(0.26)(2.59)***(2.47)**(3.14)***(3.05)***
Financial openness−0.004−0.003
(−1.67)*(−0.34)
Average years of schooling0.005

(1.72)*
0.005

(1.55)
Population growth−0.705−0.554
(−2.08)**(−1.60)
Population size0.0120.009
(1.73)*(1.64)
Initial/U.S. income−0.027−0.025
(−2.26)**(−1.93)*
Lagged hard peg−0.033−0.033
(−3.15)***(−2.44)**
Lagged intermediate0.0170.032
regime(0.82)(0.83)
APD lagged−0.032
intermediate regime(−0.84)
Observations516516505505493493516516420420
R-squared0.230.150.200.070.030.220.160.310.30
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia, T-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia, T-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.

Figure 9.6Growth Performance across Regimes

(Percent)

Source: Authors’ calculations.

Note: ** and *** denote statistical significance at the 5 percent and 1 percent levels, respectively.

The results for economic growth are robust to including the financial openness indicator, using lagged exchange rate regimes, or excluding small states. Using the specification of Ghosh, Gulde, and Wolf (2003) and Rogoff and others (2004) shows that exchange rate regimes do not seem to have any impact on growth performance because all coefficients are statistically insignificant and the coefficient on hard pegs becomes positive.10 However, this regression also has a low explanatory power.

Exchange rate regime choices appear to be of some relevance to explaining differences in output volatility (Table 9.5; Figure 9.7). Hard peg regimes are associated with a statistically higher output volatility compared with floating regimes; however, output volatility is only about 1 percent higher. For intermediate regimes the effect is even smaller and not significant. Similarly, output volatility in frontier and developing Asian economies with intermediate regimes is not significantly different compared with floating regimes in other countries, but floating regimes in Asian frontier economies are associated with somewhat higher output volatility (0.7 percent) compared with floating regimes in other regions.

Table 9.5Real GDP Growth Volatility
BaselineBaseline with Financial OpennessSpecificationLagged Exchange Rate RegimesExcluding Small States
Hard peg0.0090.0120.0090.0110.0380.0550.0090.012
(1.86)*(2.04)**(1.98)**(2.04)**(2.66)***(2.13)**(0.77)(0.87)
Intermediate regime0.0060.0020.004−0.0020.0140.0060.0030.003
(0.70)(0.11)(0.40)(−0.10)(1.31)(0.22)(0.37)(0.26)
APD0.0070.0070.0200.0070.006
(2.04)**(1.81)*(2.31)**(1.86)*(1.22)
APD intermediate reg ime−0.0010.002−0.007−0.006
(−0.07)(0.09)(−0.32)(−0.47)
Lagged growth volatility0.6010.5970.6070.6040.6040.5980.5710.567
(8.14)***(7.97)***(8.27)***(8.16)***(8.08)***(7.85)***(6.48)***(6.37)***
Investment ratio volume0.1990.2110.2010.2180.3040.3110.2030.2120.1800.193
(3.27)***(3.49)***(3.27)***(3.47)***(4.09)***(3.94)***(3.28)***(3.37)***(2.33)**(2.58)***
Trade openness0.001−0.0030.000−0.0060.006−0.0060.001−0.0030.000−0.003
(0.43)(−0.52)(0.10)(−0.62)(1.48)(−0.48)(0.43)(−0.50)(0.10)(−0.86)
Terms of trade growth volume−0.004−0.007−0.005−0.007−0.015−0.029−0.004−0.007−0.001−0.004
(−0.58)(−1.00)(−0.63)(−1.02)(−0.91)(−1.23)(−0.59)(−0.99)(−0.13)(−0.35)
Tax ratio−0.0120.006−0.0110.0140.0110.069−0.01110.005−0.0030.006
(−0.68)(0.14)(−0.53)(0.27)(0.36)(0.78)(−0.59)(0.14)(−0.19)(0.25)
Government balance−0.030−0.035−0.030−0.036−0.101−0.122−0.028−0.034−0.027−0.028
(−1.30)(−1.40)(−1.22)(−1.31)(−2.26)**(−1.94)*(−1.06)(−1.29)(−0.99)(−0.99)
Financial openness0.0010.007
(0.85)(1.81)*
Average years of schooling0.0010.002
(0.64)(0.94)
Population growth0.2780.430
(1.84)*(1.80)*
Initial/U.S. income−0.009−0.015
(−1.70)*(−1.41)
Lagged hard peg0.0080.011
(1.63)(1.80)*
Lagged intermediate regime0.0060.002
(0.59)(0.11)
APD lagged intermediate−0.001
regime(−0.04)
Observations518518507507495495518518422422
R-squared0.550.550.560.540.000.560.550.520.51
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia. T-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.
Source: Authors’ calculations.Note: APD = a dummy variable for frontier and developing Asia. T-statistics in parentheses. Asterisks denote statistical significance at 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.

Figure 9.7Growth Volatility Performance across Regimes

(Percent)

Source: Authors’ calculations.

Note: * and ** denote statistical significance at 10 percent and 5 percent levels, respectively.

The results for output volatility are robust to other specifications, except the exclusion of small states. The coefficient on hard peg regimes is only significant if the APD dummies are included. The effect of exchange rate regimes on output volatility may be driven in part by these small states, because all exchange rate coefficients become statistically insignificant when these countries are excluded from the sample.

To summarize, hard pegs are generally associated with lower inflation, lower growth, and higher growth volatility compared with floating regimes. Intermediate regimes are associated with better inflation performance—even better than hard pegs—but growth and growth volatility are not statistically significantly different from floating regimes. The impact of exchange rate regimes in frontier and developing Asia on inflation, growth, and growth volatility does not seem to differ from that in other regions.

Conclusion

In this chapter, we set out to explore how monetary policy is conducted across frontier and developing Asia and assess the extent to which the monetary and exchange rate regime choice a low-income country makes can influence growth and inflation outcomes. We find that frontier and developing Asia’s institutional frameworks for monetary policy remain rudimentary and that there is a general lack of operational autonomy for central banks, which helps explain the gravitation toward exchange rate targeting as a regime choice.11 The primary concern for growth over price stability and the desire for monetary policy flexibility have also led the majority of these countries to adopt a variant of intermediate exchange rate regimes with limited degrees of financial openness.

Through a set of multinomial logit regressions and robustness checks, we assessed how different exchange rate regimes impact economic performance with a focus on price stability and growth. We found that intermediate regimes appear to be the most conducive for achieving price stability both when compared across low-income countries in general and within the frontier and developing Asia subgroup during the initial period of growth takeoffs. Moreover, the intermediate regimes’ ability to ensure lower inflation has not come with a sacrifice of growth and growth volatility over time.

Appendix 1
Table A9.1Data and Definitions
VariableDescriptionSource
InflationScaled consumer price inflation (p/(1+p))WEO
Real GDP per capita growthReal GDP per capita growthWEO
Real GDP growth volatilityThree-year centered standard deviation of real GDP growthWEO
Relative sizeRatio of country’s GDP over U.S. GDPWEO
Geographical areaLand area (sq. km)WDI
International reserves to imports ratioInternational reserves in months of importsWEO
Ratio of quasi-money to moneyRatio of quasi-money to moneyIFS
Trade opennessSum of exports and imports of goods and services (percent of GDP)WEO
Landlocked countryDummy equal to 1 if a country is landlocked
IslandDummy equal to 1 if a country is an island
Money growthBroad money growthWEO
Real GDP growthReal GDP growthWEO
Investment ratioGross fixed investment (percent of GDP)WEO
Terms-of-trade growthTerms-of-trade growthWEO
Government balanceGeneral government balance (percent of GDP)WEO
Tax ratioGeneral government revenue (percent of GDP)WEO
Financial opennessFinancial opennessChinn and
Ito (2008)
Average years of schoolingExpected years of schoolingWDI
Population growthPopulation growthWEO
Population sizeLog of total populationWEO
Initial/U.S. incomeLog of ratio of per capita GDP to U.S. per capita GDP in 1990WEO
Exchange rate regimeHard peg includes exchange arrangement with no separate legal tender and currency board arrangement; intermediate regime includes conventional peg to a single currency, conventional peg to a composite, pegged exchange rate within horizontal bands, crawling peg and crawling band; floating regime includes managed floating with no predetermined path for the exchange rate and independently floating; based on methodology before 2008.AREAER
Source: Authors’ compilation.Note: AREAER = IMF, Annual Report on Exchange Arrangements and Exchange Reserves; IFS = IMF, International Finance Statistics database; WDI = World Bank, World Development Indicators; WEO = IMF, World Economic Outlook database.
Source: Authors’ compilation.Note: AREAER = IMF, Annual Report on Exchange Arrangements and Exchange Reserves; IFS = IMF, International Finance Statistics database; WDI = World Bank, World Development Indicators; WEO = IMF, World Economic Outlook database.
Table A9.2List of Countries
AfghanistanDjiboutiMadagascarSolomon Islands
AlbaniaDominicaMalawiSomalia
AngolaEritreaMaldivesSri Lanka
ArmeniaEthiopiaMaliSt. Lucia
AzerbaijanGambia, TheMauritaniaSt. Vincent and the Grenadines
BangladeshGeorgiaMoldovaSudan
BeninGhanaMongoliaTajikistan
BhutanGrenadaMozambiqueTanzania
BoliviaGuineaMyanmarTimor-Leste
Burkina FasoGuinea-BissauNepalTogo
BurundiGuyanaNicaraguaTonga
CambodiaHaitiNigerUganda
CameroonHondurasNigeriaUzbekistan
Cape VerdeIndiaPakistanVanuatu
Central African RepublicKenyaPapua New GuineaVietnam
ChadKiribatiRwandaYemen
ComorosKyrgyz RepublicSamoaZambia
Congo, Dem. Rep.Lao P.D.R.São Tomé and PríncipeZimbabwe
Congo, Rep.LesothoSenegal
Cote d’IvoireLiberiaSierra Leone
Note: The sample includes all countries on the Poverty Reduction Growth Trust (PRGT) list as of 2008.
Note: The sample includes all countries on the Poverty Reduction Growth Trust (PRGT) list as of 2008.
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1Frontier and developing Asia comprises 11 countries: Bangladesh, Bhutan, Cambodia, Lao P.D.R., Maldives, Mongolia, Myanmar, Nepal, Papua New Guinea, Timor-Leste, and Vietnam.
2The trilemma index reflects the well-known “impossible trinity,” which posits a trade-off between two of the following three policy dimensions: monetary independence (or domestic monetary control), exchange rate stability, and financial openness (Aizenman, Chinn, and Ito 2008).
3Cambodia is the most dollarized of the three, with foreign currency deposits estimated at over 80 percent of broad money as of early 2013.
4Other work analyzing the effects of exchange rate regimes on inflation and growth include among others Levy-Yeyati and Sturzenegger (2001, 2003), Bailliu, Lafrance, and Perrault. (2003), Courdert and Dubert (2005), Bleaney and Francisco (2007), Petreski (2009), Harms and Kretschmann (2009), and Ghosh, Ostry, and Tsangarides (2010). See Rogoff and others (2004) for an overview of the earlier literature.
5Table A9.2 lists all countries included in this analysis.
6The adjusted probabilities for the exchange rate regimes from the multinomial regression are used as instruments for the exchange rate regime, while the other control variables are not instrumented (including lags of other control variables because their instruments does not change the results much in most cases).
7Variables having a significant impact for exchange rate regime choice include relative size (for hard pegs), the international reserves to imports ratio, the ratio of quasimoney to money (for intermediate regimes), and the dummies for landlocked countries (for intermediate regimes) and islands. The variables mainly have the expected signs. For example, smaller countries or countries that are islands are more likely to have a hard peg.
8For the financial openness indicator we use the financial openness measure from Chinn and Ito (2008).
9Determinants beside the exchange rate regime dummies include money growth, real GDP growth, trade openness, the government balance, and terms-of-trade shocks.
10The determinants include the investment ratio, trade openness, terms-of-trade shocks, the tax ratio, the government balance, years of schooling, population growth, population size, and initial income compared with U.S. income.
11A table that shows the main provisions of central bank legislation as they relate to monetary policy frameworks for the frontier and developing Asian economies in this chapter is available. “Download Supplemental Material in Excel”, “Download Supplemental Material in PDF format”.

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